Feature tracking systems are generally known, in which tracking of an identified person or object in a captured scene is performed based on established image processing techniques. For example, one well known technique for object shape modelling is Active Shape Modelling (ASM), as discussed for example in “Lip Reading Using Shape, Shading And Scale”, Mathews, Cootes, Cox, Harvey and Bangham, and “An Introduction To Active Shape Models”, Tim Cootes. Another well known technique for object appearance modeling is Active Appearance Modelling (AAM), as discussed for example, in “Active Appearance Models”, Cootes, Edwards and Taylor. The applicant's prior applications GB2518589, GB2516739 and GB2517270 discuss particular techniques for modelling and tracking face features in images. However, such known feature tracking systems lack the accuracy and processing efficiency required for real-time tracking and augmentation of fingernails in captured image data.
Techniques for tracking fingers are also generally known, such as WO2005091125 (Eyesight Mobile Technologies) discusses finger detection for input of user commands based on a multi-stage segmentation process to identify a stable set of contiguous pixels representing the finger. However, in practice, the inventors have found that image pixel color segmentation is able to provide a rough estimation of location and pose of fingers in an image, which may be sufficient for gesture-based user input systems, but this technique alone is not adequate for applications that require greater accuracy and robustness, for example to enable a better user experience.
What is desired are improved techniques for more robust and efficient finger nail tracking in captured images.